Comment by haldujai
3 years ago
I don’t understand your overall point here as this is pretty much how the current system works.
> It is possible to take those probabilities and to talk about the expected number needed to treat (NNT) for a medication, the expected side effect profile, how many people might live and how many might die.
NNT > NNH = efficacy. To calculate these the trials need to be done, which is not the case for experimental therapies as they have undetermined benefits and harms (hence why they’re in trial).
The choice here is between conventional options that have known benefits/harms, however crappy they may be, with something that has unknown values.
Trials are done in multiple phases, with a progressively wider population. There is a point where we consider a drug to still be unproven, but safe enough for human trials.
I think that situations like TFA make a compelling case for selectively broadening access, for some drugs and some pathologies. The characterization of a choice between something proven and something with unknown values is too coarse and not a good model.
Clinical trials are very expensive, drug development as a field tends to move forward with what it thinks will have a chance of making it through. While most new drugs indeed fail (the large majority of them), in diseases with very poor prognosis like OP's cancer, I think we would benefit from still looking at the tradeoff as a decision under uncertainty, instead of a complete unknown. Even with less data than we would otherwise want.
Looking at experimental therapies as completely undetermined leads to a binary choice. There is supporting evidence that allows those therapies to move forward with experimental trials in the first place. The counterfactual of not treating patients with poor prognosis being what it is, my overall point is that treating experimental drugs as total unknowns with benefits and harms that cannot be quantified until the full process is finished is not consistent with the knowledge that, even after all trials are completed, this is still a uncertain statistical result, only with slightly more data than before.
In other words, we are always working with partial unknowns so when the prognosis is bad a larger unknown may be good overall and save lives, even though it wouldn't be acceptable otherwise.
> While most new drugs indeed fail (the large majority of them), in diseases with very poor prognosis like OP's cancer, I think we would benefit from still looking at the tradeoff as a decision under uncertainty, instead of a complete unknown. Even with less data than we would otherwise want.
Which is literally what just happened with osimertinib for NSCLC. It was approved for clinical use and was implemented without any overall survival data.
Safe for clinical trial means the harms are considered safe, has little to no relevance for efficacy.
Once again you’re ignoring the fact that there are (almost) always alternative treatments that have been proven to prolong life.
No one is offering nothing to poor prognosis patients.
From the blog post:
> Monday I’m starting chemotherapy, but that’s almost certainly going to fail, because a CT scan shows four to six new gross tumors, four in my neck and two, possibly, in my lungs.
In someone with such an aggressive disease everything is almost certainly going to fail, experimental or not. Chemotherapy will buy some time. Who knows what an mRNA treatment will do but there’s certainly no (not little, no) evidence that it will be curative.
You're right that there are alternatives, and there is an existing standard of care. I don't think I'm ignoring that. Let me clarify, I am not saying that patients with poor prognosis are being offered nothing. They are being offered standard of care.
I think sticking with standard of care until new drugs have gone through the full, current process may be net negative under the current process, and considering the counterfactual especially for patients with poor prognosis.
Chemoterapy will buy some time with certainty, but in expectations broadening access even slightly means we can gain confidence in the experimental treatments that do work slightly sooner, and that improves the standard of care for everyone. Experimental drugs sometimes do work, and it would be bias to only look at the risks while sweeping aside the potential upside.
Consider what happens a few years from now with the current system and with a system that selectively broadens access in some cases, when the early data seems to support the risk/reward. Even if most new medications fail, the cost of delaying those few therapy that will happen to work is much larger than the risk being paid by the trial population. That's because only a few people participate in trials, but everyone benefits from the results. This is why we have trials at all.
In someone with an aggressive disease such as OP, that person may very likely benefit from having that choice. Today they may choose to buy some time with _relative_ certainty, knowing that chemo has very heavy side effects and that they may not enjoy very much of that remaining time. But they may not choose to try some experimental treatments, even when the risk/reward seems reasonable according to early data, even though that may result in a small chance of success, and certainly data that will help bring therapies quicker to more people.
The benefit of experimental treatment is not just to the individual participating in the experiment. Part of the benefit, that helps justifies the risk, is the idea that a fraction of the treatments will be worthwhile. Slowing down trials is safer in the sense that no one will be responsible for anyone losing their chance at chemo or dying, but it creates the exact kind of invisible deaths in expectation that TFA talks about.
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